#83 · Primary category: LLM Application Frameworks

langchainrb

agents ai-agents artificial-intelligence machine-learning ml rubyml vector-search

Build LLM-powered applications in Ruby

Project last updated:08/26/26

GitHub Stars

2.0K

Forks

265

Contributors

115

License

MIT

Why we included this project

Ruby shops that want LLM features without rebuilding their stack will find this one of the few mature options in the language. It wraps a long list of providers (Anthropic, OpenAI, Google Gemini, AWS Bedrock, Ollama, and more) behind a single Ruby interface, so swapping backends usually means changing one class instead of rewriting call sites. Beyond completions, it includes embeddings, vector search, RAG pipelines, output parsers, prompt management, and assistant-style chat bots, so a fairly complete application can come out of one gem. The companion Rails gem and a dedicated evaluation module give a real path toward production integration and testing. If your team is already on Ruby and just starting to figure out how to adopt LLM tooling, this is worth checking before you default to a Python service.

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